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This study presents for the first time the SWB-J index, a subjectivewell-being indicator for Japan based on Twitter data. The index is composed byeight dimensions of subjective well-being and is estimated relying on Twitterdata by using human supervised sentiment analysis. The index is then comparedwith the analogous SWB-I index for Italy, in order to verify possible analogiesand cultural differences. Further, through structural equation models, a causalassumption is tested to see whether the economic and health conditions of thecountry influence the well-being latent variable and how this latent dimensionaffects the SWB-J and SWB-I indicators. It turns out that, as expected, theeconomic and health welfare is only one aspect of the multidimensionalwell-being that is captured by the Twitter-based indicator.

On a Japanese Subjective Well-Being Indicator Based on Twitter data